Genetic Algorithm Based Tabu Search Method for Solving Unit Commitment Problem with Cooling –– Banking Constraints

This paper presents a new approach to solving the short-term unit commitment problem using the genetic algorithm based tabu search method with cooling and banking constraints. The objective of this paper is to find the generation scheduling such that the total operating cost can be minimized, when subjected to a variety of constraints. This also means that it is desirable to find the optimal generating unit commitment in the power system for the next H hours. A power station with seven generating units in India demonstrates the effectiveness of the proposed approach; extensive studies have also been performed for different power systems consisting of IEEE 10, 26, 34 generating units. Numerical results are shown comparing the cost solutions and computation time obtained by the genetic algorithm, tabu search method and other conventional methods.